Travail Noté 3

SCI-1402: Projet en science des données

Nom, prénom: Paquet-Blanchette, Hugues

Question 1 (10 points)

a) (2 points)

Importer le fichier MapMonde.geojson. Les fichiers de format *.geojson se lisent comme des fichiers shapefile (*.shp). N’oublier pas de charger les bibliothèques nécessaires à la réalisation de ce travail: sf, tmap.

# Installer les librairies si nécessaires
if (!require("geojsonio")) install.packages("geojsonio")

## Loading required package: geojsonio

## Registered S3 method overwritten by 'geojsonsf':
##   method        from   
##   print.geojson geojson

## 
## Attaching package: 'geojsonio'

## The following object is masked from 'package:base':
## 
##     pretty

if (!require("leaflet")) install.packages("leaflet")

## Loading required package: leaflet

if (!require("dbscan")) install.packages("dbscan")

## Loading required package: dbscan

## Warning: package 'dbscan' was built under R version 4.3.3

## 
## Attaching package: 'dbscan'

## The following object is masked from 'package:stats':
## 
##     as.dendrogram

if (!require("sf")) install.packages("sf")

## Loading required package: sf

## Warning: package 'sf' was built under R version 4.3.3

## Linking to GEOS 3.13.0, GDAL 3.8.5, PROJ 9.5.1; sf_use_s2() is TRUE

if (!require("dplyr")) install.packages("dplyr")

## Loading required package: dplyr

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(readr)
library(dplyr)
library(dbscan)
library(leaflet)
library(sf)
library(geojsonio)
library(RColorBrewer)

# Lire les données
setwd("~/Desktop/Teluq/SCI-1402/Data/")
df <- read.csv("resultat_sf.csv", sep = ",", header = TRUE, encoding = "UTF-8")

df_clean <- df %>%
  filter(!is.na(Longitude), !is.na(Latitude)) %>%
  mutate(Longitude = as.numeric(Longitude),
         Latitude = as.numeric(Latitude))

coords <- df_clean %>%
  select(Longitude, Latitude) %>%
  as.matrix()

# Paramètres DBSCAN
eps_values <- seq(0.04, 0.06, by = 0.02)
minPts_values <- seq(30, 40, by = 10)

# Créer la carte Leaflet
carte <- leaflet() %>%
  addTiles(group = "Base") %>%
  addWMSTiles(
    baseUrl = "https://servicescarto.mern.gouv.qc.ca/pes/services/Territoire/SDA_WMS/MapServer/WMSServer",
    layers = "Région administrative",
    options = WMSTileOptions(format = "image/png", transparent = TRUE),
    attribution = "© MERN - Gouvernement du Québec",
    group = "Contours SDA"
  )

# Liste pour garder le nom des groupes
group_names <- c()

pal <- colorNumeric(palette = "YlOrRd", domain = df_clean$n_points, na.color = "gray")


# Générer les itérations de clustering
for (eps in eps_values) {
  for (minPts in minPts_values) {
    label <- paste0("eps=", eps, "_minPts=", minPts)
    group_names <- c(group_names, label)
    
    # Appliquer DBSCAN
    db <- dbscan(coords, eps = eps, minPts = minPts)
    df_iter <- df_clean %>%
      mutate(cluster = as.factor(db$cluster))
    
    # Ajouter le nombre de points par cluster
    cluster_counts <- df_iter %>%
      count(cluster, name = "n_points")
    df_iter <- df_iter %>%
      left_join(cluster_counts, by = "cluster")
    
    # Ajouter à la carte dans un groupe spécifique
    carte <- carte %>%
      addCircleMarkers(
        data = df_iter,
        lng = ~Longitude,
        lat = ~Latitude,
        color = ~ifelse(cluster == 0, "gray", RColorBrewer::brewer.pal(2, "Set1")[as.integer(cluster)]),
        radius = ~ifelse(cluster == 0, 1, 4),
        fillOpacity = 0.8,
        stroke = FALSE,
        group = label,
        label = ~paste("Cluster:", cluster, "<br/>Nb points:", n_points)
      )
  }
}

## Warning in RColorBrewer::brewer.pal(2, "Set1"): minimal value for n is 3, returning requested palette with 3 different levels

## Warning in RColorBrewer::brewer.pal(2, "Set1"): minimal value for n is 3, returning requested palette with 3 different levels
## Warning in RColorBrewer::brewer.pal(2, "Set1"): minimal value for n is 3, returning requested palette with 3 different levels
## Warning in RColorBrewer::brewer.pal(2, "Set1"): minimal value for n is 3, returning requested palette with 3 different levels
## Warning in RColorBrewer::brewer.pal(2, "Set1"): minimal value for n is 3, returning requested palette with 3 different levels
## Warning in RColorBrewer::brewer.pal(2, "Set1"): minimal value for n is 3, returning requested palette with 3 different levels
## Warning in RColorBrewer::brewer.pal(2, "Set1"): minimal value for n is 3, returning requested palette with 3 different levels
## Warning in RColorBrewer::brewer.pal(2, "Set1"): minimal value for n is 3, returning requested palette with 3 different levels

# Ajouter le contrôle des couches avec baseGroups
carte <- carte %>%
  addLayersControl(
    baseGroups = group_names,
    overlayGroups = c("Contours SDA"),
    options = layersControlOptions(collapsed = FALSE)
  ) %>%
  hideGroup(setdiff(group_names, group_names[1]))  # Cacher tous sauf le 1er

# Afficher la carte
carte